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Assessment of body fat composition in crossbred Angus × Nellore using biometric measurements.Journal of animal science, 95 12
( Cominotte, A., A. F. A.Fernandes, J. R. R.Dorea, G. J. M.Rosa, M. M.Ladeira, E. H. C. B.van Cleef, G. L.Pereira, W. A.Baldassini, and O. R.Machado Neto. 2020. Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases. Livest. Sci. 232:1–10. doi:10.1016/j.livsci.2019.103904)
Cominotte, A., A. F. A.Fernandes, J. R. R.Dorea, G. J. M.Rosa, M. M.Ladeira, E. H. C. B.van Cleef, G. L.Pereira, W. A.Baldassini, and O. R.Machado Neto. 2020. Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases. Livest. Sci. 232:1–10. doi:10.1016/j.livsci.2019.103904Cominotte, A., A. F. A.Fernandes, J. R. R.Dorea, G. J. M.Rosa, M. M.Ladeira, E. H. C. B.van Cleef, G. L.Pereira, W. A.Baldassini, and O. R.Machado Neto. 2020. Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases. Livest. Sci. 232:1–10. doi:10.1016/j.livsci.2019.103904, Cominotte, A., A. F. A.Fernandes, J. R. R.Dorea, G. J. M.Rosa, M. M.Ladeira, E. H. C. B.van Cleef, G. L.Pereira, W. A.Baldassini, and O. R.Machado Neto. 2020. Automated computer vision system to predict body weight and average daily gain in beef cattle during growing and finishing phases. Livest. Sci. 232:1–10. doi:10.1016/j.livsci.2019.103904
The aim of present study was to compare in vivo and post mortem methods for estimating the empty body (EB) and carcass chemical compositions of Simmental lactating and growing cattle. Indirect methods were calibrated against the direct post mortem reference determination of chemical compositions of EB and carcass, determined after grinding and analyzing the water, lipid, protein, mineral masses, and energy content. The indirect methods applied to 12 lactating cows and 10 of their offspring were ultrasound (US), half-carcass and 11th rib dual-energy X-ray absorptiometry (DXA) scans, subcutaneous and perirenal adipose cell size (ACS), and dissection of the 11th rib. Additionally, three-dimensional (3D) images were captured for 8 cows. Multiple linear regressions with leave-one-out-cross-validations were tested between predictive variables derived from the methods tested, and the EB and carcass chemical compositions. Partial least square regressions were used to estimate body composition with morphological traits measured on 3D images. Body weight (BW) alone estimated the EB and carcass composition masses with a root mean squared error of prediction (RMSEP) for the EB from 1 kg for minerals to 12.4 kg for lipids, and for carcass from 0.9 kg for minerals to 7.8 kg for water. Subcutaneous adipose tissue thickness measured by US was the most accurate in vivo predictor when associated with BW to estimate chemical composition, with the EB lipid mass RMSEP = 11 kg and R2 = 0.75; carcass water mass RMSEP = 6 kg and R2 = 0.98; and carcass energy content RMSEP = 236 MJ and R2 = 0.91. Post mortem, carcass lipid mass was best estimated by half-carcass DXA scan (RMSEP = 2 kg, R2 = 0.98), 11th rib DXA scan (RMSEP = 3 kg, R2 = 0.96), 11th rib dissection (RMSEP = 4 kg, R2 = 0.92), and perirenal ACS (RMSEP = 6 kg, R2 = 0.79) in this respective order. The results obtained by 11th rib DXA scan were accurate and close to the half-carcass DXA scan with a reduction in scan time. Morphological traits from 3D images delivered promising estimations of the cow EB and carcass chemical component masses with an error less than 13 kg for the EB lipid mass and than 740 MJ for the EB energy. Future research is required to test the 3D imaging method on a larger number of animals to confirm and quantify its interest in estimating body composition in living animals.
Translational Animal Science – Oxford University Press
Published: Jun 10, 2022
Keywords: body composition; dual-energy X-ray absorptiometry; ruminant; three-dimensional imaging; ultrasound
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